I recommend you do not try to average a set of components, because your result may be not be accurate. The best way to find an overall average is to average the entire data set.
EXAMPLE: You have three columns of ten numbers each with an average listed at the bottom of each, say A11, B11, and C11. There are two ways you can solve this:
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No, it is not. Example: the average of (5 and 7) is 6, and the average of (50, 60 and 70) is 60, but if we add all five numbers we have 192, so the overall average is 192 divided by 5 = 38.4 and the reason for that is we have more and bigger numbers in the second set.
it is grades
less than 60 pounds
Averages are called measures of central tendency because they represent a central point or typical value within a dataset. They summarize a large set of data with a single value that reflects the general trend or distribution, making it easier to understand and compare different datasets. Common types of averages, such as the mean, median, and mode, provide insights into the overall behavior of the data, highlighting its central location.
Oh, dude, okay, so like, a resultant vector is the overall effect of two or more vectors combined, while a component vector is just one of the vectors that make up the resultant. It's like saying the whole pizza is the resultant, and the pepperoni and cheese slices are the component vectors. So, basically, the resultant is the big picture, and the components are just the pieces that make it up.